/*********************************************************************************
This code is provided for internal research and development purposes by Huawei solely,
in accordance with the terms and conditions of the research collaboration agreement of May 7, 2020.
Any further use for commercial purposes is subject to a written agreement.
 *  OKVIS - Open Keyframe-based Visual-Inertial SLAM
 *  Copyright (c) 2015, Autonomous Systems Lab / ETH Zurich
 *  Copyright (c) 2016, ETH Zurich, Wyss Zurich, Zurich Eye
 *
 *  Redistribution and use in source and binary forms, with or without
 *  modification, are permitted provided that the following conditions are met:
 *
 *   * Redistributions of source code must retain the above copyright notice,
 *     this list of conditions and the following disclaimer.
 *   * Redistributions in binary form must reproduce the above copyright notice,
 *     this list of conditions and the following disclaimer in the documentation
 *     and/or other materials provided with the distribution.
 *   * Neither the name of Autonomous Systems Lab / ETH Zurich nor the names of
 *     its contributors may be used to endorse or promote products derived from
 *     this software without specific prior written permission.
 *
 *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 *  AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 *  IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 *  ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
 *  LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
 *  CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
 *  SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
 *  INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 *  CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
 *  ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 *  POSSIBILITY OF SUCH DAMAGE.
 *
 *  Created on: Jul 27, 2015
 *      Author: Stefan Leutenegger (s.leutenegger@imperial.ac.uk)
 *    Modified: Zurich Eye
 *********************************************************************************/

#include <ze/nlls/local_parameterization_additional_interfaces.hpp>

#pragma diagnostic push
#pragma GCC diagnostic ignored "-Wdeprecated-declarations"
// Eigen 3.2.7 uses std::binder1st and std::binder2nd which are deprecated since c++11
// Fix is in 3.3 devel (http://eigen.tuxfamily.org/bz/show_bug.cgi?id=872).
#include <ceres/ceres.h>
#include <Eigen/Core>
#pragma diagnostic pop

namespace ze {
namespace nlls {

// Verifies the correctness of a inplementation.
bool LocalParamizationAdditionalInterfaces::verify(
    const double* x_raw, double purturbation_magnitude) const
{
  const ceres::LocalParameterization* casted =
      dynamic_cast<const ceres::LocalParameterization*>(this);
  if (!casted)
  {
    return false;
  }
  // verify plus/minus
  Eigen::VectorXd x(casted->GlobalSize());
  memcpy(x.data(), x_raw, sizeof(double) * casted->GlobalSize());
  Eigen::VectorXd delta_x(casted->LocalSize());
  Eigen::VectorXd x_plus_delta(casted->GlobalSize());
  Eigen::VectorXd delta_x2(casted->LocalSize());
  delta_x.setRandom();
  delta_x *= purturbation_magnitude;
  casted->Plus(x.data(), delta_x.data(), x_plus_delta.data());
  this->Minus(x.data(), x_plus_delta.data(), delta_x2.data());
  if ((delta_x2 - delta_x).norm() > 1.0e-12)
  {
    return false;
  }

  // plusJacobian numDiff
  Eigen::Matrix<double, -1, -1, Eigen::RowMajor> J_plus_num_diff(
      casted->GlobalSize(), casted->LocalSize());
  const double dx = 1.0e-9;
  for (int i = 0; i < casted->LocalSize(); ++i)
  {
    Eigen::VectorXd delta_p(casted->LocalSize());
    delta_p.setZero();
    delta_p[i] = dx;
    Eigen::VectorXd delta_m(casted->LocalSize());
    delta_m.setZero();
    delta_m[i] = -dx;

    // reset
    Eigen::VectorXd x_p(casted->GlobalSize());
    Eigen::VectorXd x_m(casted->GlobalSize());
    memcpy(x_p.data(), x_raw, sizeof(double) * casted->GlobalSize());
    memcpy(x_m.data(), x_raw, sizeof(double) * casted->GlobalSize());
    casted->Plus(x.data(), delta_p.data(), x_p.data());
    casted->Plus(x.data(), delta_m.data(), x_m.data());
    J_plus_num_diff.col(i) = (x_p - x_m) / (2 * dx);
  }

  // verify lift
  Eigen::Matrix<double, -1, -1, Eigen::RowMajor> J_plus(casted->GlobalSize(),
                                                        casted->LocalSize());
  Eigen::Matrix<double, -1, -1, Eigen::RowMajor> J_lift(casted->LocalSize(),
                                                        casted->GlobalSize());
  casted->ComputeJacobian(x_raw, J_plus.data());
  ComputeLiftJacobian(x_raw, J_lift.data());
  Eigen::MatrixXd identity(casted->LocalSize(), casted->LocalSize());
  identity.setIdentity();
  if (((J_lift * J_plus) - identity).norm() > 1.0e-6)
  {
    return false;
  }

  // verify numDiff jacobian
  if ((J_plus - J_plus_num_diff).norm() > 1.0e-6)
  {
    return false;
  }

  // everything fine...
  return true;
}

} // namespace nlls
} // namespace ze

